The seroprevalence of Rocky Mountain spotted fever in shelter dogs in Harris County

Rocky Mountain spotted fever (RMSF) is a tick-borne illness caused by the bacteria Rickettsia rickettsii, with infections occurring in humans and dogs. The prominent tick vector of RMSF, Dermacantor variabilis, and another potential vector, Rhipacephalus sanguineus, are prevalent in Texas. The goal of this study was to determine the prevalence of past infections by testing for IgG antibodies to R. rickettsii in dogs in an animal shelter in Harris County using an immunofluorescence assay (IFA) test. We found that 12.6% (24) of 191 dogs tested had a positive IFA test at 1:64 serum dilution, indicating infection at some time in the past. We also sampled the ticks present on dogs in the animal shelter to understand the prevalence of potential vector species. Of a total of 58 ticks, 86% were D. variabilis and the remaining 14% were R. sanguineus. The results of this study demonstrate that RMSF has the potential to be, and may already be, endemic to the Harris County area. Public health actions such as heightened surveillance and education that RMSF is present would be appropriate in the Harris County area.^

The eukaryotic cellular stress response: Biochemical and genetic analyses in Saccharomyces cerevisiae

All cells must have the ability to deal with a variety of environmental stresses. Failure to correctly adapt to and/or protect against adverse stress conditions can lead to cell death. In humans, stress response defects have been linked to a number of neurodegenerative diseases and cancer, underscoring the importance of developing a fundamental understanding of the eukaryotic stress response.^ In an effort to characterize cellular response to high temperature stress, I identified and described one member of a novel gene family— RTR1. I show that the RTR1 gene and its protein product genetically and biochemically interact with core subunits of the RNA polymerase II enzyme. Appropriately, loss of RTR1 results in defective transcription from multiple promoters. These data provide evidence that Rtr1, which is essential under stress conditions, acts as a key regulator of transcription.^ In addition to transcriptional regulation, cells deal with many stressors by inducing molecular chaperones. Molecular chaperones are ubiquitous in all living cells and bind unfolded or damaged proteins and catalyze refolding or degradation. Hsp90 is a unique chaperone because it targets specific clients—typically signaling proteins—for maturation. While it has been shown that Sse1, the yeast Hsp110, is a critical regulator of the Hsp90 chaperone cycle, this work describes the molecular basis for that regulation. I show that Sse1 modulates Hsp90 function through regulation of Hsp70 nucleotide exchange. Further, Hsp110-type nucleotide exchange factors (NEFs) appear to have a specific role in modulating Hsp90 function in this manner. Finally, in addition to Hsp110, the eukaryotic cytosol contains two other types of Hsp70 NEF: Snl1 (BAG-domain protein) and Fes1 (HspBP1-like protein). I investigated the cellular roles of these NEFs to better understand the reason that eukaryotic cells contain three distinct protein families that perform the same biochemical function. I show that while cytsolic Hsp70 NEFs have some degree of functional overlap, they also exhibit striking divergence. Taken together, the work presented in this dissertation provides a more detailed understanding of the eukaryotic stress response. ^

Identification and characterization of virulence determinants in the Lyme disease spirochete Borrelia burgdorferi

Borrelia burgdorferi is the etiological agent of Lyme disease, the most common tick-borne disease in the United States. Although the most frequently reported symptom is arthritis, patients can also experience severe cardiac, neurologic, and dermatologic abnormalities. The identification of virulence determinants in infectious B. burgdorferi strains has been limited by their slow growth rate, poor transformability, and general lack of genetic tools. The present study demonstrates the use of transposon mutagenesis for the identification of infectivity-related factors in infectious B. burgdorferi, examines the potential role for chemotaxis in mammalian infection, and describes the development of a novel method for the analysis of recombination events at the Ids antigenic variation locus. A pool of Himar1 mutants was isolated using an infectious B. burgdorferi clone and the transposon vector pMarGent. Clones exhibiting reduced infectivity in mice possessed insertions in virulence determinants putatively involved in host survival and dissemination. These results demonstrated the feasibility of extensive transposon mutagenesis studies for the identification of additional infectivity-related factors. mcp-5 mutants were chosen for further study to determine the role of chemotaxis during infection. Animal studies indicated that mcp-5 mutants exhibited a reduced infectivity potential, and suggested a role for mcp-5 during the early stages of infection. An in vitro phenotype for an mcp-5 mutant was not detected. Genetic complementation of an mcp-5 mutant resulted in restoration of Mcp-5 expression in the complemented clone, as demonstrated by western blotting, but the organisms were not infectious in mice. We believe this result is a consequence of differences in expression between genes located on the linear chromosome and genes present on the circular plasmid used for trans-complementation. Overall, this work implicates mcp-5 as an important determinant of mammalian infectivity. Finally, the development of a computer-assisted method for the analysis of recombination events occurring at the B. burgdorferi vls antigenic variation locus has proven highly valuable for the detailed examination of vls gene conversion. The studies described here provide evidence for the importance of chemotaxis during infection in mice and demonstrate advances in both genetic and computational approaches for the further characterization of the Lyme disease spirochete. ^

The influence of socioeconomic status on the relationship between diabetes and amputations: A systematic review of the literature

This paper synthesizes the current knowledge available regarding the impact of socioeconomic status on diabetes and amputations. In September 2009, searches in the OVID Medline and PubMed databases were performed using keywords associated with race/ethnicity, educational level, insurance status, veteran status, low income, diabetes, and lower extremity amputation. Articles published between 1996 and the search date were used. The pertinent articles were analyzed, summarized, and synthesized. ^ The majority of the articles agreed that African American, American Indian, and Latino minorities experience significantly higher rates of diabetes-related lower extremity amputation (LEA) when compared to whites. Few articles suggested that the disparity experienced by minorities and others of low SES was due to biology; most articles link it to a combination of lower income, lower educational attainment, uninsured or underinsured status, and a greater prevalence of detrimental health behaviors such as smoking. These, in turn, are linked to decreased knowledge of self-care, delayed health care seeking, delayed diagnoses and treatment, discrimination, and low quality health care. Interventions focused on patient education, established regimens of treatment, foot care, and control of diabetes have been shown to be effective, although none have lowered the rate of diabetes-related LEA to rates found in the general population.^

Genetic variability and the hypothalamic control of energy balance

Background. Obesity is a major health problem throughout the industrialized world. Despite numerous attempts to curtail the rapid growth of obesity, its incidence continues to rise. Therefore, it is crucial to better understand the etiology of obesity beyond the concept of energy balance.^ Aims. The first aim of this study was to first investigate the relationship between eating behaviors and body size. The second goal was to identify genetic variation associated with eating behaviors. Thirdly, this study aimed to examine the joint relationships between eating behavior, body size and genetic variation.^ Methods. This study utilized baseline data ascertained in young adults from the Training Interventions and Genetics of Exercise (TIGER) Study. Variables assessed included eating behavior (Emotional Eating Scale, Eating Attitudes Test-26, and the Block98 Food Frequency Questionnaire), body size (body mass index, waist and hip circumference, waist/hip ratio, and percent body fat), genetic variation in genes implicated related to the hypothalamic control of energy balance, and appropriate covariates (age, gender, race/ethnicity, smoking status, and physical activity. For the genetic association analyses, genotypes were collapsed by minor allele frequency, and haplotypes were estimated for each gene. Additionally, Bayesian networks were constructed in order to determine the relationships between genetic variation, eating behavior and body size.^ Results. We report that the EAT-26 score, Caloric intake, percent fat, fiber intake, HEAT index, and daily servings of vegetables, meats, grains, and fats were significantly associated with at least one body size measure. Multiple SNPs in 17 genes and haplotypes from 12 genes were tested for their association with body size. Variation within both DRD4 and HTR2A was found to be associated with EAT-26 score. In addition, variation in the ghrelin gene (GHRL) was significantly associated with daily Caloric intake. A significant interaction between daily servings of grains and the HEAT index and variation within the leptin receptor gene (LEPR) was shown to influence body size.^ Conclusion. This study has shown that there is a substantial genetic component to eating behavior and that genetic variation interacts with eating behavior to influence body size.^

S100A4 is a molecular mediator of endometrial carcinoma invasion

The molecular mechanisms of endometrail cancer invasion are poorly understood. S100A4, a member of the S100 Ca2+-binding protein family, was identified by oligonucleotide microarray qRT-PCR, and IHC, to be highly overexpressed in invasive endometrial carcinomas compared to non-invasive tumors. HEC-1A endometrial cancer cells transfected with S100A4 siRNA had undetectable S100A4 protein, decreased migration and invasion. The mechanism of S100A4 upregulation in endometrial cancer remains unclear. Methylation of the S100A4 gene was detected in benign endometrial glands and grade 1 tumors with no S100A4 expression. In contrast, grade 3 endometrioid tumors with high S100A4 expression showed no methylation of the gene. 5-Aza-2'-deoxycytidine, an inhibitor of DNA methyltransferase, induced the expression of S100A4 in the less invasive EC cell line, KLE, in which the S100A4 gene is hypermethylated and minimally expressed. S100A4 was induced during TGF-β1-triggered cell scattering in HEC-1A cells, in which S100A4 was demethylated. Transfection of HEC-1A cells with S100A4 siRNA significantly reduced the effect of TGF-β1 on basal migration and invasion. Our preliminary data suggested that this upregulation was mediated by the transcription factor Snail. One Snail binding consensus site was found in the region where DNA methylation was closely correlated with S100A4 gene expression. Chromatin immunoprecipitation assay confirmed the binding of Snail to this consensus site in HEC-1A cells. In SPEC2 endometrial cancer cells, loss of Snail leads to repressed S100A4 gene expression. Similar to S100A4, Snail was overexpressed in aggressive endometrial tumors. Our study suggested that the S100A4 gene was demethylated and further upregulated by the TGF-β1 and Snail pathway in invasive endometrial cancer. S100A4 could potentially serve as a good molecular marker for invasiveness and a target for therapeutic intervention for advanced endometrial cancer. ^

An evaluation of a Lake Houston tributary, Cypress Creek, for contamination and water quality

Introduction. Lake Houston serves as a reservoir for both recreational and drinking water for residents of Houston, Texas, and the metropolitan area. The Texas Commission on Environmental Quality (TCEQ) expressed concerns about the water quality and increasing amounts of pathogenic bacteria in Lake Houston (3). The objective of this investigation is to evaluate water quality for the presence of bacteria, nitrates, nitrites, carbon, phosphorus, dissolved oxygen, pH, turbidity, suspended solids, dissolved solids, and chlorine in Cypress Creek. The aims of this project are to analyze samples of water from Cypress Creek and to render a quantitative and graphical representation of the results. The collected information will allow for a better understanding of the aqueous environment in Cypress Creek.^ Methods. Water samples were collected in August 2009 and analyzed in the field and at UTSPH laboratory by spectrophotometry and other methods. Mapping software was utilized to develop novel maps of the sample sites using coordinates attained with the Global Positioning System (GPS). Sample sites and concentrations were mapped using Geographic Information System (GIS) software and correlated with permitted outfalls and other land use characteristic.^ Results. All areas sampled were positive for the presence of total coliform and Escherichia coli (E. coli). The presences of other water contaminants varied at each location in Cypress Creek but were under the maximum allowable limits designated by the Texas Commission on Environmental Quality. However, dissolved oxygen concentrations were elevated above the TCEQ limit of 5.0 mg/L at majority of the sites. One site had near-limit concentration of nitrates at 9.8 mg/L. Land use above this site included farm land, agricultural land, golf course, parks, residential neighborhoods, and nine permitted TCEQ effluent discharge sites within 0.5 miles upstream.^ Significance. Lake Houston and its tributary, Cypress Creek, are used as recreational waters where individuals may become exposed to microbial contamination. Lake Houston also is the source of drinking water for much of Houston/Harris and Galveston Counties. This research identified the presence of microbial contaminates in Cypress Creek above TCEQ regulatory requirements. Other water quality variables measured were in line with TCEQ regulations except for near-limit for nitrate at sample site #10, at Jarvis and Timberlake in Cypress Texas.^

Impact of maternal Tdap vaccination on pertussis infection in young infants

Undiagnosed infected mothers often are the source of pertussis illness in young infants. The Centers for Disease Control and Prevention (CDC) recommends Tdap vaccine for post-partum women before hospital discharge. This intervention has been implemented at Ben Taub General Hospital (BTGH) in Houston, TX since January 2008. Our objective was to compare the proportion of infants born at BTGH and developing pertussis to the total number of pertussis cases before and after the intervention. Methods. We conducted a cross-sectional comparative study between the pre-intervention (7/2000 to 12/2007) and post-intervention (1/2008 to 5/2009) periods. Information on pertussis diagnosis was determined using ICD-9 codes, infection control records, and molecular microbiology reports from Texas Children's Hospital (TCH) and BTGH. Only patients ≤ 6 months of age with laboratory-confirmed B. pertussis infection were included in the study. Results. 481 infants had pertussis illness; 353 (73.3%) during pre-intervention and 128 (26.6%) during post-intervention years. The groups were comparable in all measures including age (median 73 vs. 62.5 days; p=0.08), gender (males 54.2%; p=0.47), length of hospitalization (median 9.8 vs. 4 9.5 days; p=0.5), outcomes (2 deaths in each period; p=0.28) and pertussis illness at TCH (95.2% vs. 95.3%; p=0.9). The proportion of pertussis patients born at BTGH, and thus amenable to protection by the intervention, was not statically different between the two periods after adjusting for age, gender and ethnicity (7.3% vs. 9.3%; an OR=1.05, 95% CI 0.5-2.1, p=0.88). Conclusions. Vaccinating only mothers with Tdap in the post-partum period does not reduce the proportion of pertussis in infants age ≤ 6 months. Efforts should be directed at Tdap immunization of not only mothers, but also all household and key contacts of newborns to protect them against pertussis illness before the primary DTaP series is completed.^

Systematic interpretation of molecular beacon polymerase chain reaction for identifying rpoB mutations in Mycobacterium tuberculosis isolates with mixed resistant and susceptible bacteria

Detection of multidrug-resistant tuberculosis (MDR-TB), a frequent cause of treatment failure, takes 2 or more weeks to identify by culture. RIF-resistance is a hallmark of MDR-TB, and detection of mutations in the rpoB gene of Mycobacterium tuberculosis using molecular beacon probes with real-time quantitative polymerase chain reaction (qPCR) is a novel approach that takes ≤2 days. However, qPCR identification of resistant isolates, particularly for isolates with mixed RIF-susceptible and RIF-resistant bacteria, is reader dependent and limits its clinical use. The aim of this study was to develop an objective, reader-independent method to define rpoB mutants using beacon qPCR. This would facilitate the transition from a research protocol to the clinical setting, where high-throughput methods with objective interpretation are required. For this, DNAs from 107 M. tuberculosis clinical isolates with known susceptibility to RIF by culture-based methods were obtained from 2 regions where isolates have not previously been subjected to evaluation using molecular beacon qPCR: the Texas–Mexico border and Colombia. Using coded DNA specimens, mutations within an 81-bp hot spot region of rpoB were established by qPCR with 5 beacons spanning this region. Visual and mathematical approaches were used to establish whether the qPCR cycle threshold of the experimental isolate was significantly higher (mutant) compared to a reference wild-type isolate. Visual classification of the beacon qPCR required reader training for strains with a mixture of RIF-susceptible and RIF-resistant bacteria. Only then had the visual interpretation by an experienced reader had 100% sensitivity and 94.6% specificity versus RIF-resistance by culture phenotype and 98.1% sensitivity and 100% specificity versus mutations based on DNA sequence. The mathematical approach was 98% sensitive and 94.5% specific versus culture and 96.2% sensitive and 100% specific versus DNA sequence. Our findings indicate the mathematical approach has advantages over the visual reading, in that it uses a Microsoft Excel template to eliminate reader bias or inexperience, and allows objective interpretation from high-throughput analyses even in the presence of a mixture of RIF-resistant and RIF-susceptible isolates without the need for reader training.^

HPV vaccine coverage in Texas counties: An application of multilevel, small area estimation

Health departments, research institutions, policy-makers, and healthcare providers are often interested in knowing the health status of their clients/constituents. Without the resources, financially or administratively, to go out into the community and conduct health assessments directly, these entities frequently rely on data from population-based surveys to supply the information they need. Unfortunately, these surveys are ill-equipped for the job due to sample size and privacy concerns. Small area estimation (SAE) techniques have excellent potential in such circumstances, but have been underutilized in public health due to lack of awareness and confidence in applying its methods. The goal of this research is to make model-based SAE accessible to a broad readership using clear, example-based learning. Specifically, we applied the principles of multilevel, unit-level SAE to describe the geographic distribution of HPV vaccine coverage among females aged 11-26 in Texas.^ Multilevel (3 level: individual, county, public health region) random-intercept logit models of HPV vaccination (receipt of ≥ 1 dose Gardasil® ) were fit to data from the 2008 Behavioral Risk Factor Surveillance System (outcome and level 1 covariates) and a number of secondary sources (group-level covariates). Sampling weights were scaled (level 1) or constructed (levels 2 & 3), and incorporated at every level. Using the regression coefficients (and standard errors) from the final models, I simulated 10,000 datasets for each regression coefficient from the normal distribution and applied them to the logit model to estimate HPV vaccine coverage in each county and respective demographic subgroup. For simplicity, I only provide coverage estimates (and 95% confidence intervals) for counties.^ County-level coverage among females aged 11-17 varied from 6.8-29.0%. For females aged 18-26, coverage varied from 1.9%-23.8%. Aggregated to the state level, these values translate to indirect state estimates of 15.5% and 11.4%, respectively; both of which fall within the confidence intervals for the direct estimates of HPV vaccine coverage in Texas (Females 11-17: 17.7%, 95% CI: 13.6, 21.9; Females 18-26: 12.0%, 95% CI: 6.2, 17.7).^ Small area estimation has great potential for informing policy, program development and evaluation, and the provision of health services. Harnessing the flexibility of multilevel, unit-level SAE to estimate HPV vaccine coverage among females aged 11-26 in Texas counties, I have provided (1) practical guidance on how to conceptualize and conduct modelbased SAE, (2) a robust framework that can be applied to other health outcomes or geographic levels of aggregation, and (3) HPV vaccine coverage data that may inform the development of health education programs, the provision of health services, the planning of additional research studies, and the creation of local health policies.^

Elucidating the IGFBP2 signaling pathway in glioma development and progression

Diffuse gliomas are highly lethal central nervous system malignancies which, unfortunately, are the most common primary brain tumor and also the least responsive to the very few therapeutic modalities currently available to treat them. IGFBP2 is a newly recognized oncogene that is operative in multiple cancer types, including glioma, and shows promise for a targeted therapeutic approach. Elevated IGFBP2 expression is present in high-grade glioma and correlates with poor survival. We have previously demonstrated that IGFBP2 induces glioma development and progression in a spontaneous glioma mouse model, which highlighted its significance and potential for future therapy. However, we did not yet know the key physiological pathways associated with this newly characterized oncogene. We first evaluated human glioma genomics data harnessed from the publicly available Rembrandt source to identify major pathways associated with IGFBP2 expression. Integrin and ILK, among other cell migration and invasion-related pathways, were the most prominently associated. We confirmed that these pathways are regulated by IGFBP2 in glioma cells lines, and demonstrated that 1) IGFBP2 activates integrin α5β1, leading to the activation of key pathways important in glioma; 2) IGFBP2 mediates cell migration pathways through ILK; and 3) IGFBP2 activates NF-kB via an integrin α5 interaction. We then sought to determine whether this was a physiologically active signaling pathway in vivo by assessing its ability to induce glioma progression in the RCAS/tv-a spontaneous glioma mouse model. We found that ILK is a key downstream mediator of IGFBP2 that is required for the induction of glioma progression. Most significantly, a genetic therapeutic approach revealed that perturbation of any point in the pathway thwarted tumor progression, providing strong evidence that targeting the key players could potentially produce a significant benefit for human glioma patients. The elucidation of this signaling pathway is a critical step, since efforts to create a small molecule drug targeting IGFBP2 have so far not been successful, but a number of inhibitors of the other pathway constituents, including ILK, integrin and NF-kB, have been developed.

IDENTIFICATION AND CHARACTERIZATION OF DISTINCT POPULATIONS OF CLONOGENIC BONE MARROW STROMAL CELLS CAPABLE OF TRANSFERRING THE HEMATOPOIETIC MICROENVIRONMENT IN VIVO AND SUPPORTING LT-HSCs IN VITRO

Bone marrow (BM) stromal cells are ascribed two key functions, 1) stem cells for non-hematopoietic tissues (MSC) and 2) as components of the hematopoietic stem cell niche. Current approaches studying the stromal cell system in the mouse are complicated by the low yield of clonogenic progenitors (CFU-F). Given the perivascular location of MSC in BM, we developed an alternative methodology to isolate MSC from mBM. An intact ‘plug’ of bone marrow is expelled from bones and enzymatically disaggregated to yield a single cell suspension. The recovery of CFU-F (1917.95+199) reproducibly exceeds that obtained using the standard BM flushing technique (14.32+1.9) by at least 2 orders of magnitude (P<0.001; N = 8) with an accompanying 196-fold enrichment of CFU-F frequency. Purified BM stromal and vascular endothelial cell populations are readily obtained by FACS. A detailed immunophenotypic analysis of lineage depleted BM identified PDGFRαβPOS stromal cell subpopulations distinguished by their expression of CD105. Both subpopulations retained their original phenotype of CD105 expression in culture and demonstrate MSC properties of multi-lineage differentiation and the ability to transfer the hematopoietic microenvironment in vivo. To determine the capacity of either subpopulation to support long-term multi-lineage reconstituting HSCs, we fractionated BM stromal cells into either the LinNEGPDGFRαβPOSCD105POS and LINNEGPDGFRαβPOSCD105LOW/- populations and tested their capacity to support LT-HSC by co-culturing each population with either 1 or 10 HSCs for 10 days. Following the 10 day co-culture period, both populations supported transplantable HSCs from 10 cells/well co-cultures demonstrating high levels of donor repopulation with an average of 65+23.6% chimerism from CD105POS co-cultures and 49.3+19.5% chimerism from the CD105NEG co-cultures. However, we observed a significant difference when mice were transplanted with the progeny of a single co-cultured HSC. In these experiments, CD105POS co-cultures (100%) demonstrated long-term multi- lineage reconstitution, while only 4 of 8 mice (50%) from CD105NEG -single HSC co-cultures demonstrated long-term reconstitution, suggesting a more limited expansion of functional stem cells. Taken together, these results demonstrate that the PDGFRαβCD105POS stromal cell subpopulation is distinguished by a unique capacity to support the expansion of long-term reconstituting HSCs in vitro.

Multivariate methods for correlated effects sizes

Current statistical methods for estimation of parametric effect sizes from a series of experiments are generally restricted to univariate comparisons of standardized mean differences between two treatments. Multivariate methods are presented for the case in which effect size is a vector of standardized multivariate mean differences and the number of treatment groups is two or more. The proposed methods employ a vector of independent sample means for each response variable that leads to a covariance structure which depends only on correlations among the $p$ responses on each subject. Using weighted least squares theory and the assumption that the observations are from normally distributed populations, multivariate hypotheses analogous to common hypotheses used for testing effect sizes were formulated and tested for treatment effects which are correlated through a common control group, through multiple response variables observed on each subject, or both conditions.^ The asymptotic multivariate distribution for correlated effect sizes is obtained by extending univariate methods for estimating effect sizes which are correlated through common control groups. The joint distribution of vectors of effect sizes (from $p$ responses on each subject) from one treatment and one control group and from several treatment groups sharing a common control group are derived. Methods are given for estimation of linear combinations of effect sizes when certain homogeneity conditions are met, and for estimation of vectors of effect sizes and confidence intervals from $p$ responses on each subject. Computational illustrations are provided using data from studies of effects of electric field exposure on small laboratory animals. ^

Bayesian inference and its application to meta-analysis of epidemiologic data

In Part One, the foundations of Bayesian inference are reviewed, and the technicalities of the Bayesian method are illustrated. Part Two applies the Bayesian meta-analysis program, the Confidence Profile Method (CPM), to clinical trial data and evaluates the merits of using Bayesian meta-analysis for overviews of clinical trials.^ The Bayesian method of meta-analysis produced similar results to the classical results because of the large sample size, along with the input of a non-preferential prior probability distribution. These results were anticipated through explanations in Part One of the mechanics of the Bayesian approach. ^

A Bayesian analysis for spatial processes with application to mapping

In geographical epidemiology, maps of disease rates and disease risk provide a spatial perspective for researching disease etiology. For rare diseases or when the population base is small, the rate and risk estimates may be unstable. Empirical Bayesian (EB) methods have been used to spatially smooth the estimates by permitting an area estimate to "borrow strength" from its neighbors. Such EB methods include the use of a Gamma model, of a James-Stein estimator, and of a conditional autoregressive (CAR) process. A fully Bayesian analysis of the CAR process is proposed. One advantage of this fully Bayesian analysis is that it can be implemented simply by using repeated sampling from the posterior densities. Use of a Markov chain Monte Carlo technique such as Gibbs sampler was not necessary. Direct resampling from the posterior densities provides exact small sample inferences instead of the approximate asymptotic analyses of maximum likelihood methods (Clayton & Kaldor, 1987). Further, the proposed CAR model provides for covariates to be included in the model. A simulation demonstrates the effect of sample size on the fully Bayesian analysis of the CAR process. The methods are applied to lip cancer data from Scotland, and the results are compared. ^